A founder showed me a dashboard last month with a metric I hadn't seen before: cost per completed task, the dollar amount it takes an agent to answer one real request, start to finish. Not total spend. Not cost per user. Cost per task. Once I understood why he tracked it that specifically, I couldn't stop noticing how many AI products don't.
Gross margin stops being a useful signal once compute enters the unit economics.
For most of software's history, 80% gross margin meant healthy, and 40% usually meant a services business dressed up as software, because the cost of serving one more user was close to zero. AI-native products are running closer to 52% gross margin on average now, against the 70-80% range that used to be the baseline for traditional SaaS. That's the shape of the whole category, a direct result of every response calling out to a model that costs real money to run, every single time.
The tell is that the margin number stops telling you anything on its own. Two products can report the same 55% gross margin, one well-optimized and improving, the other one growth spurt away from watching its economics worsen with scale. You can't see the difference without going one level deeper.
